Medication-induced Pulmonary Injury: A Scenario- and Pattern-based Approach to a Perplexing Problem.

Medication-induced pulmonary injury (MIPI) is a complex medical condition that has become increasingly common yet remains stubbornly difficult to diagnose. Diagnosis can be aided by combining knowledge of the most common imaging patterns caused by MIPI with awareness of which medications a patient may be exposed to in specific clinical settings. The authors describe six imaging patterns commonly associated with MIPI: sarcoidosis-like, diffuse ground-glass opacities, organizing pneumonia, centrilobular ground-glass nodules, linear-septal, and fibrotic. Subsequently, the occurrence of these patterns is discussed in the context of five different clinical scenarios and the medications and medication classes typically used in those scenarios. These scenarios and medication classes include the rheumatology or gastrointestinal clinic (disease-modifying antirheumatic agents), cardiology clinic (antiarrhythmics), hematology clinic (cytotoxic agents, tyrosine kinase inhibitors, retinoids), oncology clinic (immune modulators, tyrosine kinase inhibitors, monoclonal antibodies), and inpatient service (antibiotics, blood products). Additionally, the article draws comparisons between the appearance of MIPI and the alternative causes of lung disease typically seen in those clinical scenarios (eg, connective tissue disease-related interstitial lung disease in the rheumatology clinic and hydrostatic pulmonary edema in the cardiology clinic). Familiarity with the most common imaging patterns associated with frequently administered medications can help insert MIPI into the differential diagnosis of acquired lung disease in these scenarios. However, confident diagnosis is often thwarted by absence of specific diagnostic tests for MIPI. Instead, a working diagnosis typically relies on multidisciplinary consensus. ©RSNA, 2021.

Hedgehog signaling pathway molecules and ALDH1A1 expression in early-stage non-small cell lung cancer.

INTRODUCTION: The Hedgehog Signaling Pathway (HHSP) has been implicated in the development of multiple cancers. HHSP activation may primarily be hedgehog ligand-dependent in non-small cell lung cancer (NSCLC); while a subset may be ligand-independent. In this study NSCLC primary tumors were used to identify correlations between multiple biomarkers thought to be involved in the HHSP and the clinical outcomes of patients with NSCLC. Identification of such correlations could be used to aid in NSCLC treatment and predicting patient prognosis. METHODS: A tissue microarray representing 248 clinically annotated stage I-II NSCLC cases was stained using immunohistochemistry (IHC) and scored for HHSP proteins namely, SHH, PTCH1, SMO, GLI1, and GLI2; as well as, ALDH1A1, a putative cancer stem cell marker. Data was analyzed for correlation between IHC staining, EGFR and KRAS mutations, and clinical characteristics including relapse-free survival (RFS) and overall survival (OS). RESULTS: In adenocarcinoma, there were significant correlations of IHC expression between SHH and downstream HHSP receptor SMO (p=0.017) and transcription factor GLI1 (p=0.001), while SMO correlated with GLI1 (p=0.007). In squamous cell carcinoma, SHH significantly correlated with GLI2 protein expression (p=0.003). After multiple testing correction, there was no significant correlation between any of the six markers and RFS or OS. CONCLUSIONS: Key downstream components of the HHSP show correlation with sonic hedgehog ligand (SHH) expression, suggesting that ligand-dependent signaling is more prevalent in primary NSCLC tumors. Surprisingly, in early-stage NSCLC, there were no significant correlations between HHSP proteins or ALDH1A1 and RFS or OS.

Biomarkers associated with metastasis of lung cancer to brain predict patient survival.

MicroRNAs influence cell physiology; alteration in miRNA regulation can be implicated in carcinogenesis and disease progression. Generally, one miRNA is predicted to regulate several hundred genes, and as a result, miRNAs could serve as a better classifier than gene expression. We combine validated miRNA expression values with imaging features to classify NSCLC brain mets from non-brain mets and identify possible biomarkers of brain mets. This research involves comprehensive miRNA expression profiling, evaluation of normalisation techniques and combination of miRNA with imaging features FDG-PET/CT and CT Scan. The biomarkers were validated on an independent data set to predict potential brain mets.

MicroRNA-328 is associated with (non-small) cell lung cancer (NSCLC) brain metastasis and mediates NSCLC migration.

Brain metastasis (BM) can affect ∼ 25% of nonsmall cell lung cancer (NSCLC) patients during their lifetime. Efforts to characterize patients that will develop BM have been disappointing. microRNAs (miRNAs) regulate the expression of target mRNAs. miRNAs play a role in regulating a variety of targets and, consequently, multiple pathways, which make them a powerful tool for early detection of disease, risk assessment, and prognosis. We investigated miRNAs that may serve as biomarkers to differentiate between NSCLC patients with and without BM. miRNA microarray profiling was performed on samples from clinically matched NSCLC from seven patients with BM (BM+) and six without BM (BM-). Using t-test and further qRT-PCR validation, eight miRNAs were confirmed to be significantly differentially expressed. Of these, expression of miR-328 and miR-330-3p were able to correctly classify BM+ vs. BM- patients. This classifier was used on a validation cohort (n = 15), and it correctly classified 12/15 patients. Gene expression analysis comparing A549 parental and A549 cells stably transfected to over-express miR-328 (A549-328) identified several significantly differentially expressed genes. PRKCA was one of the genes over-expressed in A549-328 cells. Additionally, A549-328 cells had significantly increased cell migration compared to A549 cells, which was significantly reduced upon PRKCA knockdown. In summary, miR-328 has a role in conferring migratory potential to NSCLC cells working in part through PRKCA and with further corroboration in additional independent cohorts, these miRNAs may be incorporated into clinical treatment decision making to stratify NSCLC patients at higher risk for developing BM.

MicroRNA 92a-2*: a biomarker predictive for chemoresistance and prognostic for survival in patients with small cell lung cancer.

PURPOSE: Although the majority of patients with small cell lung cancer (SCLC) respond to initial chemotherapy, those with disease progression at first response assessment (chemoresistance) have inferior outcomes. There is a need for predictive biomarkers to aid investigators in designing future clinical trials that better stratify patients beyond standard clinical and laboratory parameters and to identify new treatments for this patient subpopulation. We hypothesized that tumor microRNAs (miRNAs) could serve as predictive biomarkers for chemoresistance and prognostic biomarkers for survival of patients with SCLC treated with systemic chemotherapy. PATIENTS AND METHODS: SCLC samples annotated with clinical characteristics and baseline comorbidities were available. miRNA microarray profiling was performed on diagnostic SCLC tumor samples, and analysis was performed using XenoBase, a data integration and discovery tool. Confirmation of the top 16 miRNA candidates was performed using quantitative real-time polymerase chain reaction followed by analyses to determine clinical and miRNA biomarkers associated with chemoresistance and survival. RESULTS: miRNAs significantly associated with chemoresistance were miR-92a-2* (p = 0.010), miR-147 (p = 0.018), and miR-574-5p (p = 0.039). By stepwise multivariate analysis, only gender and miR-92a-2* contributed significantly to survival (p = 0.023) and (p = 0.015), respectively. Baseline comorbidities were not associated with chemoresistance or survival. CONCLUSIONS: Higher tumor miR-92a-2* levels are associated with chemoresistance and with decreased survival in patients with SCLC. Tumor miR-92a-2* may have application in screening patients with SCLC at risk for de novo chemoresistance in an effort to design more tailored clinical trials for this subpopulation. Further validation in independent sample sets is warranted.